HUSNUZAN AND QUARTER-LIFE CRISIS IN STUDENTS OF RADEN MAS SAID ISLAMIC STATE UNIVERSITY SURAKARTA
Bibliographic record
Abstract
Adolescence is a crucial stage in the human developmental phase because adolescents typically experience various problems. One of the problems is the quarter-life crisis (QLC). QLC is a problem related to anxiety about multiple roles that have yet to be completed in the adolescence phase, such as university, work, and marriage. Literature mentioned that QLC can be buffered by husnuzan. However, the authors found that some university students in Raden Mas Said Islamic State University Surakarta/Universitas Islam Negeri (UIN) Raden Mas Said Surakarta who are in the adolescence phase and implementing husnuzan still experience QLC. Thus, the present study aimed to explain the correlation between husnuzan and a quarter-life crisis. The study used a correlational quantitative approach. Therefore, data collection instruments were in the form of Likert scales. Husnuzan and QLC instruments were validated by six experts to ensure the validity of every item. Additionally, the two instruments were tested resulting in a reliability coefficient of 0.941 for the QLC scale and 0.908 for the husnuzan scale. The study involved 300 students of UIN Raden Mas Said Surakarta aged 21-25 years old. An analysis with regression analysis showed F=178.523 and β=-0.612 with p<0.01. In other words, there is an effect of husnuzan on quarter-life crisis among students of UIN Raden Mas Said Surakarta. In the context of da'wah, this research is expected to be a reference theme for preachers targeting young people and preachers' efforts to overcome the problems of young people.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".